-----------------------------------------------------------------------------------------------------
      name:  <unnamed>
       log:  C:\Users\afang\Documents\PSRM_BallotSecrecy\PublicReplicationArchive\02_Analysis.log
  log type:  text
 opened on:  31 Mar 2017, 14:47:23

. /*----------------------------------------------------------------------
>  
>  REPLICATION FILE FOR
>  Gerber, Alan S., Gregory A. Huber, Albert H. Fang, and Andrew Gooch. (Forthcoming)
>  "Non-Governmental Campaign Communication Providing Ballot Secrecy Assurances Increases
>    Turnout: Results from Two Large Scale Experiments"
>  Political Science Research and Methods
>  
>  FILE:                  02_Analysis.do
>  DESCRIPTION:   Performs analysis reported in tables/figures in main text
>  DATE:                  14 Dec 2016
>  VERSION:               1.0
> 
> ----------------------------------------------------------------------*/
. use PublicReplicationData, clear

. 
. 
. /*-----------------------
> TABLE 1:
> ITT estimates
> -----------------------*/
.         local treat_vars = " t3_1 t3_2 "

. 
.         * loop over under/over 55 subgroups
.         forvalues u = 1(-1)0 {
  2.                 
.                 * define analysis sample condition
.                 local select = "under55==`u' & never_voted==1 & flag_hh_mixed_nv != 1"
  3.                 
.                 * define ipw to use
.                 local ipw = "ipw_t3_pooled_nv"
  4.                 
.                 * construct state-by-cov interactions
.                 foreach st in GA LA MI NC TX {
  5.                 foreach v in age age2 d_race_black d_race_hisp d_race_other d_mar_married d_mar_
> unknown d_gend_female {
  6.                         gen Z_`st'_`v' = d_st_`st' * `v'
  7.                         quietly sum Z_`st'_`v' if `select'
  8.                         if (r(sd) == . | r(sd) == 0) {
  9.                                 drop Z_`st'_`v'
 10.                                 }
 11.                         }
 12.                 }
 13.                 
.                 if (`u' == 1) {                 // UNDER 55 ANALYSIS
 14.                 
.                         * (1) all covs, NO state-by-cov interactions, with hhsize dummies, with ipw
> , with cluster SE
.                         reg voted14 `treat_vars' age age2 age_miss hhsize2 hhsize3 hhsize4 d_* [awe
> ight=`ipw'] if `select', vce(cluster hhid)
 15.                         local adjr2 = e(r2_a)
 16.                         qui sum voted14 [aweight=`ipw'] if t2==0 & e(sample)
 17.                         local c_turnout = r(mean)
 18.                         lincom t3_1 - t3_2
 19.                         local coltag = "Under 55 Experiment,Base Specification"
 20.                         outreg2 using "Table1_ITTEstimates.xls", se bracket dec(3) label ctitle(
> "`coltag'") drop(Z*)   ///
>                                 addstat("Adjusted R-squared", `adjr2', "Control Group Mean Turnout"
> , `c_turnout') addtext( "State-Covariate Interactions?", N, "Weighted?", Y, "Household-Level Cluste
> red SE?", Y) replace
 21.                         
.                         * (2) all covs, YES state-by-cov interactions, with hhsize dummies, with ip
> w, with cluster SE   
.                         reg voted14 `treat_vars' age age2 age_miss hhsize2 hhsize3 hhsize4 d_* Z_* 
> [aweight=`ipw'] if `select', vce(cluster hhid)
 22.                         local adjr2 = e(r2_a)
 23.                         qui sum voted14 [aweight=`ipw'] if t2==0 & e(sample)
 24.                         local c_turnout = r(mean)
 25.                         local coltag = "Under 55 Experiment,With State-By-,Covariate,Interaction
> s"
 26.                         outreg2 using "Table1_ITTEstimates.xls", se bracket dec(3) label ctitle(
> "`coltag'") drop(Z*)   ///
>                                 addstat("Adjusted R-squared", `adjr2', "Control Group Mean Turnout"
> , `c_turnout') addtext( "State-Covariate Interactions?", Y, "Weighted?", Y, "Household-Level Cluste
> red SE?", Y) append
 27.                         
.                         * (3) all covs, NO state-by-cov interactions, with hhsize dummies, WITHOUT 
> ipw, WITHOUT cluster SE
.                         reg voted14 `treat_vars' age age2 age_miss hhsize2 hhsize3 hhsize4 d_* if `
> select'
 28.                         local adjr2 = e(r2_a)
 29.                         qui sum voted14 if t2==0 & e(sample)
 30.                         local c_turnout = r(mean)
 31.                         local coltag = "Under 55 Experiment,Unweighted,And Without,HH-Level,Clus
> tered SE"
 32.                         outreg2 using "Table1_ITTEstimates.xls", se bracket dec(3) label ctitle(
> "`coltag'") drop(Z*)   ///
>                                 addstat("Adjusted R-squared", `adjr2', "Control Group Mean Turnout"
> , `c_turnout') addtext( "State-Covariate Interactions?", N, "Weighted?", N, "Household-Level Cluste
> red SE?", N) append
 33.                         
.                 }
 34.                 else {                                  // OVER 55 ANALYSIS
 35.                 
.                         * (1) all covs, NO state-by-cov interactions, with hhsize dummies, with ipw
> , with cluster SE
.                         reg voted14 `treat_vars' age age2 age_miss hhsize2 hhsize3 hhsize4 d_* [awe
> ight=`ipw'] if `select', vce(cluster hhid)
 36.                         local adjr2 = e(r2_a)
 37.                         qui sum voted14 [aweight=`ipw'] if t2==0 & e(sample)
 38.                         local c_turnout = r(mean)
 39.                         local coltag = "Over 55 Experiment,Base Specification"
 40.                         outreg2 using "Table1_ITTEstimates.xls", se bracket dec(3) label ctitle(
> "`coltag'") drop(Z*)   ///
>                                 addstat("Adjusted R-squared", `adjr2', "Control Group Mean Turnout"
> , `c_turnout') addtext( "State-Covariate Interactions?", N, "Weighted?", Y, "Household-Level Cluste
> red SE?", Y) append
 41.                 
.                         * (2) all covs, YES state-by-cov interactions, with hhsize dummies, with ip
> w, with cluster SE           
.                         reg voted14 `treat_vars' age age2 age_miss hhsize2 hhsize3 hhsize4 d_* Z_* 
> [aweight=`ipw'] if `select', vce(cluster hhid)
 42.                         local adjr2 = e(r2_a)
 43.                         qui sum voted14 [aweight=`ipw'] if t2==0 & e(sample)
 44.                         local c_turnout = r(mean)
 45.                         local coltag = "Over 55 Experiment,With State-By-,Covariate,Interactions
> "
 46.                         outreg2 using "Table1_ITTEstimates.xls", se bracket dec(3) label ctitle(
> "`coltag'") drop(Z*)   ///
>                                 addstat("Adjusted R-squared", `adjr2', "Control Group Mean Turnout"
> , `c_turnout') addtext( "State-Covariate Interactions?", Y, "Weighted?", Y, "Household-Level Cluste
> red SE?", Y) append
 47.                 
.                         * (3) all covs, NO state-by-cov interactions, with hhsize dummies, WITHOUT 
> ipw, WITHOUT cluster SE
.                         reg voted14 `treat_vars' age age2 age_miss hhsize2 hhsize3 hhsize4 d_* if `
> select'
 48.                         local adjr2 = e(r2_a)
 49.                         qui sum voted14 if t2==0 & e(sample)
 50.                         local c_turnout = r(mean)
 51.                         local coltag = "Over 55 Experiment,Unweighted,And Without,HH-Level,Clust
> ered SE"
 52.                         outreg2 using "Table1_ITTEstimates.xls", se bracket dec(3) label ctitle(
> "`coltag'") drop(Z*)   ///
>                                 addstat("Adjusted R-squared", `adjr2', "Control Group Mean Turnout"
> , `c_turnout') addtext( "State-Covariate Interactions?", N, "Weighted?", N, "Household-Level Cluste
> red SE?", N) append
 53.                                                 
.                 }
 54. 
.                 * drop interactions
.                 drop Z_*
 55.                 
.         }
(sum of wgt is   8.4617e+05)

Linear regression                               Number of obs     =    281,929
                                                F(19, 270344)     =     212.51
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0279
                                                Root MSE          =     .33741

                              (Std. Err. adjusted for 270,345 clusters in hhid)
-------------------------------------------------------------------------------
              |               Robust
      voted14 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------+----------------------------------------------------------------
         t3_1 |   .0095734   .0023057     4.15   0.000     .0050543    .0140926
         t3_2 |   .0078997   .0023924     3.30   0.001     .0032106    .0125888
          age |  -.0016583    .000569    -2.91   0.004    -.0027734   -.0005431
         age2 |   .0060019   .0008533     7.03   0.000     .0043294    .0076743
     age_miss |   .1615173   .0485316     3.33   0.001     .0663966     .256638
      hhsize2 |    .008422   .0040243     2.09   0.036     .0005345    .0163095
      hhsize3 |   .0206754    .018521     1.12   0.264    -.0156252     .056976
      hhsize4 |   .0504721   .0892012     0.57   0.572    -.1243598     .225304
 d_race_black |  -.0238579   .0022999   -10.37   0.000    -.0283657   -.0193502
  d_race_hisp |  -.0483115    .002258   -21.40   0.000    -.0527372   -.0438858
 d_race_other |   -.027211   .0035996    -7.56   0.000    -.0342661    -.020156
d_mar_married |   .0845626   .0036217    23.35   0.000     .0774642     .091661
d_mar_unknown |   .1580815   .0524609     3.01   0.003     .0552595    .2609034
d_gend_female |   .0136564   .0016836     8.11   0.000     .0103565    .0169563
      d_st_GA |  -.0102194   .0041007    -2.49   0.013    -.0182567    -.002182
      d_st_LA |   .0682725   .0059133    11.55   0.000     .0566826    .0798625
      d_st_MI |  -.0773945   .0037805   -20.47   0.000    -.0848041   -.0699848
      d_st_NC |   .0005737   .0043331     0.13   0.895     -.007919    .0090664
      d_st_TX |  -.0642216   .0034417   -18.66   0.000    -.0709673   -.0574759
        _cons |   .1649611   .0092654    17.80   0.000     .1468012    .1831211
-------------------------------------------------------------------------------

 ( 1)  t3_1 - t3_2 = 0

------------------------------------------------------------------------------
     voted14 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         (1) |   .0016738   .0014089     1.19   0.235    -.0010876    .0044351
------------------------------------------------------------------------------
Table1_ITTEstimates.xls
dir : seeout
(sum of wgt is   8.4617e+05)

Linear regression                               Number of obs     =    281,929
                                                F(57, 270344)     =      80.90
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0315
                                                Root MSE          =     .33681

                                   (Std. Err. adjusted for 270,345 clusters in hhid)
------------------------------------------------------------------------------------
                   |               Robust
           voted14 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------------+----------------------------------------------------------------
              t3_1 |   .0096101   .0022994     4.18   0.000     .0051035    .0141168
              t3_2 |   .0078614   .0023863     3.29   0.001     .0031842    .0125385
               age |  -.0098614   .0021935    -4.50   0.000    -.0141607   -.0055621
              age2 |   .0170721   .0033059     5.16   0.000     .0105926    .0235516
          age_miss |   .1909121   .0493418     3.87   0.000     .0942035    .2876207
           hhsize2 |   .0084366    .004004     2.11   0.035     .0005889    .0162844
           hhsize3 |   .0280949   .0183116     1.53   0.125    -.0077953     .063985
           hhsize4 |   .0590427   .0900337     0.66   0.512    -.1174209    .2355063
      d_race_black |  -.0411102   .0072959    -5.63   0.000      -.05541   -.0268104
       d_race_hisp |  -.0579626   .0115341    -5.03   0.000    -.0805691   -.0353561
      d_race_other |   -.054456   .0157054    -3.47   0.001    -.0852382   -.0236739
     d_mar_married |   .1036996   .0161841     6.41   0.000     .0719792      .13542
     d_mar_unknown |   .0341709   .0871914     0.39   0.695    -.1367218    .2050637
     d_gend_female |    .020384   .0063627     3.20   0.001     .0079132    .0328547
           d_st_GA |  -.2496145   .0416283    -6.00   0.000    -.3312049   -.1680242
           d_st_LA |  -.1985906   .0619521    -3.21   0.001    -.3200151   -.0771661
           d_st_MI |  -.0088766   .0416261    -0.21   0.831    -.0904625    .0727094
           d_st_NC |  -.1005264   .0435572    -2.31   0.021    -.1858973   -.0151555
           d_st_TX |  -.2191222   .0341847    -6.41   0.000    -.2861233   -.1521211
          Z_GA_age |   .0136575     .00277     4.93   0.000     .0082284    .0190866
         Z_GA_age2 |  -.0176102   .0041496    -4.24   0.000    -.0257434   -.0094771
 Z_GA_d_race_black |   .0230408   .0094618     2.44   0.015      .004496    .0415857
  Z_GA_d_race_hisp |    .023388   .0146937     1.59   0.111    -.0054113    .0521873
 Z_GA_d_race_other |   .0019871   .0186645     0.11   0.915    -.0345948    .0385691
Z_GA_d_mar_married |   .0168367   .0194874     0.86   0.388    -.0213582    .0550315
Z_GA_d_mar_unknown |   .1957133   .0858623     2.28   0.023     .0274255    .3640012
Z_GA_d_gend_female |   .0040675   .0081943     0.50   0.620    -.0119932    .0201281
          Z_LA_age |   .0140411   .0040047     3.51   0.000     .0061921    .0218902
         Z_LA_age2 |  -.0174236   .0058892    -2.96   0.003    -.0289663   -.0058809
 Z_LA_d_race_black |   .0309343   .0132089     2.34   0.019     .0050452    .0568234
  Z_LA_d_race_hisp |   .0100191   .0237199     0.42   0.673    -.0364713    .0565094
 Z_LA_d_race_other |   .0507481   .0288354     1.76   0.078    -.0057684    .1072647
Z_LA_d_mar_married |   .1176551   .0304967     3.86   0.000     .0578823    .1774278
Z_LA_d_mar_unknown |   .2315395   .0996839     2.32   0.020     .0361617    .4269173
Z_LA_d_gend_female |   .0085318   .0119802     0.71   0.476    -.0149491    .0320127
          Z_MI_age |  -.0048379   .0027791    -1.74   0.082     -.010285    .0006091
         Z_MI_age2 |   .0057419   .0041954     1.37   0.171     -.002481    .0139647
 Z_MI_d_race_black |   .0433344   .0093495     4.63   0.000     .0250097    .0616591
  Z_MI_d_race_hisp |   .0603253   .0151331     3.99   0.000     .0306648    .0899858
 Z_MI_d_race_other |   .1034195   .0181367     5.70   0.000      .067872     .138967
Z_MI_d_mar_married |  -.0235517   .0187022    -1.26   0.208    -.0602076    .0131042
Z_MI_d_gend_female |       .002   .0074742     0.27   0.789    -.0126492    .0166492
          Z_NC_age |    .004666   .0029774     1.57   0.117    -.0011697    .0105016
         Z_NC_age2 |  -.0031629   .0045367    -0.70   0.486    -.0120546    .0057289
 Z_NC_d_race_black |    .029086   .0100185     2.90   0.004     .0094501     .048722
  Z_NC_d_race_hisp |  -.0065315   .0145035    -0.45   0.652     -.034958     .021895
 Z_NC_d_race_other |   .0554912   .0211638     2.62   0.009     .0140108    .0969716
Z_NC_d_mar_married |   .0036596   .0217064     0.17   0.866    -.0388843    .0462034
Z_NC_d_gend_female |  -.0111725   .0085892    -1.30   0.193    -.0280072    .0056621
          Z_TX_age |   .0109242   .0023076     4.73   0.000     .0064015     .015447
         Z_TX_age2 |  -.0153064   .0034772    -4.40   0.000    -.0221216   -.0084912
 Z_TX_d_race_black |   .0024449   .0080192     0.30   0.760    -.0132725    .0181623
  Z_TX_d_race_hisp |   .0012457   .0118456     0.11   0.916    -.0219713    .0244626
 Z_TX_d_race_other |   .0077321   .0163834     0.47   0.637     -.024379    .0398431
Z_TX_d_mar_married |  -.0393554   .0168135    -2.34   0.019    -.0723094   -.0064013
Z_TX_d_mar_unknown |  -.2151702    .082194    -2.62   0.009    -.3762681   -.0540723
Z_TX_d_gend_female |  -.0139543   .0067349    -2.07   0.038    -.0271545   -.0007541
             _cons |   .2954927   .0325789     9.07   0.000     .2316389    .3593465
------------------------------------------------------------------------------------
Table1_ITTEstimates.xls
dir : seeout

      Source |       SS           df       MS      Number of obs   =   281,929
-------------+----------------------------------   F(19, 281909)   =    432.98
       Model |  949.710502        19  49.9847632   Prob > F        =    0.0000
    Residual |  32544.5609   281,909  .115443498   R-squared       =    0.0284
-------------+----------------------------------   Adj R-squared   =    0.0283
       Total |  33494.2714   281,928  .118804345   Root MSE        =    .33977

-------------------------------------------------------------------------------
      voted14 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------+----------------------------------------------------------------
         t3_1 |   .0096135   .0022913     4.20   0.000     .0051226    .0141043
         t3_2 |   .0079565   .0023717     3.35   0.001     .0033081    .0126049
          age |  -.0015441    .000391    -3.95   0.000    -.0023104   -.0007777
         age2 |   .0059109    .000572    10.33   0.000     .0047897     .007032
     age_miss |   .1463098    .026727     5.47   0.000     .0939256    .1986939
      hhsize2 |   .0102907   .0025225     4.08   0.000     .0053467    .0152346
      hhsize3 |   .0066713   .0087139     0.77   0.444    -.0104077    .0237503
      hhsize4 |  -.0228775   .0259866    -0.88   0.379    -.0738106    .0280556
 d_race_black |  -.0254202   .0016939   -15.01   0.000    -.0287402   -.0221003
  d_race_hisp |  -.0477114   .0018183   -26.24   0.000    -.0512753   -.0441476
 d_race_other |  -.0217838   .0026726    -8.15   0.000     -.027022   -.0165457
d_mar_married |   .0847556   .0023166    36.59   0.000      .080215    .0892961
d_mar_unknown |   .1917521   .0285179     6.72   0.000     .1358577    .2476464
d_gend_female |   .0141392   .0013367    10.58   0.000     .0115193     .016759
      d_st_GA |  -.0086952   .0028132    -3.09   0.002     -.014209   -.0031813
      d_st_LA |   .0720357   .0037243    19.34   0.000     .0647361    .0793352
      d_st_MI |  -.0777113   .0027537   -28.22   0.000    -.0831085   -.0723142
      d_st_NC |  -.0036573   .0029009    -1.26   0.207     -.009343    .0020284
      d_st_TX |   -.066072   .0023913   -27.63   0.000    -.0707589   -.0613852
        _cons |    .163084   .0065779    24.79   0.000     .1501916    .1759764
-------------------------------------------------------------------------------
Table1_ITTEstimates.xls
dir : seeout
(sum of wgt is   6.5866e+04)
note: t3_2 omitted because of collinearity
note: age_miss omitted because of collinearity
note: hhsize4 omitted because of collinearity
note: d_mar_unknown omitted because of collinearity

Linear regression                               Number of obs     =     32,978
                                                F(15, 32076)      =      40.00
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0520
                                                Root MSE          =     .42536

                               (Std. Err. adjusted for 32,077 clusters in hhid)
-------------------------------------------------------------------------------
              |               Robust
      voted14 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------+----------------------------------------------------------------
         t3_1 |  -.0032517    .008052    -0.40   0.686    -.0190339    .0125305
         t3_2 |          0  (omitted)
          age |   .0426482   .0076654     5.56   0.000     .0276237    .0576726
         age2 |  -.0293704   .0056311    -5.22   0.000    -.0404076   -.0183333
     age_miss |          0  (omitted)
      hhsize2 |   .1334248   .0265447     5.03   0.000     .0813962    .1854534
      hhsize3 |  -.1160507   .0815522    -1.42   0.155    -.2758961    .0437946
      hhsize4 |          0  (omitted)
 d_race_black |  -.0270966   .0116849    -2.32   0.020    -.0499994   -.0041937
  d_race_hisp |  -.0652396   .0124758    -5.23   0.000    -.0896927   -.0407865
 d_race_other |  -.1069637    .014607    -7.32   0.000    -.1355938   -.0783335
d_mar_married |   .1154799   .0131557     8.78   0.000     .0896941    .1412656
d_mar_unknown |          0  (omitted)
d_gend_female |   .0317983   .0089008     3.57   0.000     .0143524    .0492441
      d_st_GA |  -.0307132   .0186169    -1.65   0.099    -.0672031    .0057766
      d_st_LA |   .1568299   .0251046     6.25   0.000     .1076239    .2060359
      d_st_MI |   -.094701   .0195382    -4.85   0.000    -.1329966   -.0564053
      d_st_NC |    .062577   .0209346     2.99   0.003     .0215445    .1036095
      d_st_TX |  -.0856977   .0167463    -5.12   0.000    -.1185211   -.0528743
        _cons |  -1.214441   .2584514    -4.70   0.000    -1.721016   -.7078667
-------------------------------------------------------------------------------
Table1_ITTEstimates.xls
dir : seeout
(sum of wgt is   6.5866e+04)
note: t3_2 omitted because of collinearity
note: age_miss omitted because of collinearity
note: hhsize4 omitted because of collinearity
note: d_mar_unknown omitted because of collinearity

Linear regression                               Number of obs     =     32,978
                                                F(50, 32076)      =      17.45
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0614
                                                Root MSE          =     .42346

                                    (Std. Err. adjusted for 32,077 clusters in hhid)
------------------------------------------------------------------------------------
                   |               Robust
           voted14 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------------+----------------------------------------------------------------
              t3_1 |  -.0024169   .0079834    -0.30   0.762    -.0180648    .0132309
              t3_2 |          0  (omitted)
               age |   .0322593    .033307     0.97   0.333    -.0330237    .0975422
              age2 |  -.0227199   .0248654    -0.91   0.361    -.0714569    .0260172
          age_miss |          0  (omitted)
           hhsize2 |   .1294188   .0258465     5.01   0.000     .0787586     .180079
           hhsize3 |  -.1269781   .0872617    -1.46   0.146    -.2980144    .0440582
           hhsize4 |          0  (omitted)
      d_race_black |  -.0681208   .0402246    -1.69   0.090    -.1469626    .0107209
       d_race_hisp |  -.1475112   .0604653    -2.44   0.015    -.2660254    -.028997
      d_race_other |  -.2092355   .0580806    -3.60   0.000    -.3230758   -.0953953
     d_mar_married |   .1536114   .0537802     2.86   0.004     .0482001    .2590227
     d_mar_unknown |          0  (omitted)
     d_gend_female |  -.0057095   .0383658    -0.15   0.882    -.0809079     .069489
           d_st_GA |   .0957345    1.27631     0.08   0.940    -2.405882    2.597351
           d_st_LA |  -1.060982   1.795787    -0.59   0.555    -4.580793    2.458828
           d_st_MI |  -1.338245   1.304777    -1.03   0.305    -3.895658    1.219168
           d_st_NC |  -1.320779   1.371232    -0.96   0.335    -4.008447    1.366888
           d_st_TX |  -.2554693   1.158615    -0.22   0.825    -2.526399    2.015461
          Z_GA_age |  -.0050257   .0382514    -0.13   0.895         -.08    .0699485
         Z_GA_age2 |   .0031453   .0283728     0.11   0.912    -.0524665    .0587571
 Z_GA_d_race_black |   .0291201   .0501321     0.58   0.561    -.0691408    .1273809
  Z_GA_d_race_hisp |   .0984416    .073226     1.34   0.179    -.0450841    .2419672
 Z_GA_d_race_other |   .0555591    .070449     0.79   0.430    -.0825235    .1936417
Z_GA_d_mar_married |  -.0161667   .0623004    -0.26   0.795    -.1382778    .1059443
Z_GA_d_gend_female |   .0762898   .0441492     1.73   0.084    -.0102443    .1628239
          Z_LA_age |   .0265785   .0542385     0.49   0.624     -.079731     .132888
         Z_LA_age2 |  -.0178183   .0405702    -0.44   0.661    -.0973374    .0617008
 Z_LA_d_race_black |   .2320211    .064102     3.62   0.000     .1063787    .3576635
  Z_LA_d_race_hisp |   .4528473   .1003246     4.51   0.000     .2562074    .6494873
 Z_LA_d_race_other |   .3800104   .1129367     3.36   0.001     .1586503    .6013705
Z_LA_d_mar_married |   .1027444   .0742158     1.38   0.166    -.0427215    .2482102
Z_LA_d_gend_female |   .0989462   .0581782     1.70   0.089    -.0150854    .2129777
          Z_MI_age |   .0346273   .0392209     0.88   0.377    -.0422472    .1115018
         Z_MI_age2 |  -.0243696    .029105    -0.84   0.402    -.0814165    .0326773
 Z_MI_d_race_black |   .0038542   .0515924     0.07   0.940     -.097269    .1049773
  Z_MI_d_race_hisp |   .1872452   .0833192     2.25   0.025     .0239365    .3505539
 Z_MI_d_race_other |   .1753892   .0717445     2.44   0.015     .0347672    .3160112
Z_MI_d_mar_married |  -.0719105   .0819621    -0.88   0.380    -.2325593    .0887384
Z_MI_d_gend_female |   .0172454   .0499991     0.34   0.730    -.0807547    .1152454
          Z_NC_age |   .0372926   .0410026     0.91   0.363     -.043074    .1176593
         Z_NC_age2 |  -.0269939   .0303147    -0.89   0.373    -.0864119    .0324241
 Z_NC_d_race_black |   .1399299   .0552839     2.53   0.011     .0315713    .2482886
  Z_NC_d_race_hisp |   .0493908    .077294     0.64   0.523    -.1021084      .20089
 Z_NC_d_race_other |   .0901124   .0747354     1.21   0.228    -.0563718    .2365966
Z_NC_d_mar_married |   .0884584   .0700896     1.26   0.207    -.0489198    .2258367
Z_NC_d_gend_female |   .0661376   .0527326     1.25   0.210    -.0372203    .1694956
          Z_TX_age |   .0028122   .0349231     0.08   0.936    -.0656385    .0712628
         Z_TX_age2 |  -.0005886   .0260401    -0.02   0.982    -.0516283    .0504511
 Z_TX_d_race_black |   -.007042   .0436634    -0.16   0.872     -.092624      .07854
  Z_TX_d_race_hisp |   .0556071   .0623593     0.89   0.373    -.0666195    .1778338
 Z_TX_d_race_other |   .0794125    .061104     1.30   0.194    -.0403536    .1991787
Z_TX_d_mar_married |  -.0689358   .0559096    -1.23   0.218    -.1785208    .0406492
Z_TX_d_gend_female |   .0262551   .0399449     0.66   0.511    -.0520385    .1045487
             _cons |  -.7761231   1.103768    -0.70   0.482    -2.939549    1.387303
------------------------------------------------------------------------------------
Table1_ITTEstimates.xls
dir : seeout
note: t3_2 omitted because of collinearity
note: age_miss omitted because of collinearity
note: hhsize4 omitted because of collinearity
note: d_mar_unknown omitted because of collinearity

      Source |       SS           df       MS      Number of obs   =    32,978
-------------+----------------------------------   F(15, 32962)    =    122.81
       Model |  331.972372        15  22.1314915   Prob > F        =    0.0000
    Residual |  5940.17561    32,962  .180212839   R-squared       =    0.0529
-------------+----------------------------------   Adj R-squared   =    0.0525
       Total |  6272.14798    32,977  .190197652   Root MSE        =    .42451

-------------------------------------------------------------------------------
      voted14 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------+----------------------------------------------------------------
         t3_1 |    -.00318   .0078018    -0.41   0.684    -.0184718    .0121118
         t3_2 |          0  (omitted)
          age |   .0391944   .0044332     8.84   0.000     .0305051    .0478837
         age2 |  -.0270593   .0032498    -8.33   0.000     -.033429   -.0206896
     age_miss |          0  (omitted)
      hhsize2 |   .1085557   .0112605     9.64   0.000     .0864847    .1306268
      hhsize3 |   -.116946   .0867438    -1.35   0.178     -.286967     .053075
      hhsize4 |          0  (omitted)
 d_race_black |   -.030054   .0068378    -4.40   0.000    -.0434564   -.0166516
  d_race_hisp |  -.0682775   .0074579    -9.16   0.000    -.0828953   -.0536596
 d_race_other |  -.1122089   .0089068   -12.60   0.000    -.1296666   -.0947512
d_mar_married |   .1164855    .007378    15.79   0.000     .1020243    .1309466
d_mar_unknown |          0  (omitted)
d_gend_female |     .02662   .0056826     4.68   0.000     .0154819    .0377582
      d_st_GA |  -.0207286   .0104342    -1.99   0.047      -.04118   -.0002772
      d_st_LA |    .144831   .0132807    10.91   0.000     .1188003    .1708616
      d_st_MI |  -.1061356   .0112377    -9.44   0.000    -.1281618   -.0841094
      d_st_NC |   .0674591   .0113849     5.93   0.000     .0451443     .089774
      d_st_TX |  -.0966561   .0093896   -10.29   0.000    -.1150601    -.078252
        _cons |  -1.077059   .1499813    -7.18   0.000    -1.371028   -.7830905
-------------------------------------------------------------------------------
Table1_ITTEstimates.xls
dir : seeout

. 
. /*-----------------------
> TABLE 2:
> ITT estimates by state
> -----------------------*/
. 
. preserve

. 
. keep if never_voted == 1
(394 observations deleted)

. 
. * ESTIMATE ITT
. 
.         local treat_vars = " t3_1 t3_2 "

. 
.         * loop over under/over 55 subgroups
.         forvalues u = 1(-1)0 {
  2.         
.         foreach s in `"AR"' `"GA"' `"LA"' `"MI"' `"NC"' `"TX"' {
  3.         
.                 * define analysis sample condition
.                 local select = "under55==`u'"
  4.                 
.                 * define ipw to use
.                 local ipw = "ipw_t3_pooled_st_nv"
  5.                 
.                 * define dummy variables to include (exclude state dummies)
.                 local d_vars = "d_race_black d_race_hisp d_race_other d_mar_married d_mar_unknown d
> _gend_female"
  6. 
.                 /* DO NOT construct state-by-cov interactions */
.                 
.                 if (`u' == 1) {                 // UNDER 55 ANALYSIS
  7.                 
.                         if ("`s'" == "AR") {
  8.                         * (1) all covs, NO state-by-cov interactions, with hhsize dummies, with 
> ipw, with cluster SE
.                         reg voted14 `treat_vars' age age2 age_miss hhsize2 hhsize3 hhsize4 `d_vars'
>  [aweight=`ipw'] if `select' & state == "`s'", vce(cluster hhid)
  9.                         local adjr2 = e(r2_a)
 10.                         qui sum voted14 [aweight=`ipw'] if t2==0 & e(sample)
 11.                         local c_turnout = r(mean)
 12.                         outreg2 using "Table2_ITTEstimatesByState.xls", se bracket dec(3) label 
> ctitle("Under 55 Experiment,`s'") ///
>                                 addstat("Adjusted R-squared", `adjr2', "Control Group Mean Turnout"
> , `c_turnout') addtext("Weighted?", Y, "Household-Level Clustered SE?", Y) replace
 13.                         }
 14.                         else {
 15.                         * (1) all covs, NO state-by-cov interactions, with hhsize dummies, with 
> ipw, with cluster SE
.                         reg voted14 `treat_vars' age age2 age_miss hhsize2 hhsize3 hhsize4 `d_vars'
>  [aweight=`ipw'] if `select' & state == "`s'", vce(cluster hhid)
 16.                         local adjr2 = e(r2_a)
 17.                         qui sum voted14 [aweight=`ipw'] if t2==0 & e(sample)
 18.                         local c_turnout = r(mean)
 19.                         outreg2 using "Table2_ITTEstimatesByState.xls", se bracket dec(3) label 
> ctitle("Under 55 Experiment,`s'") ///
>                                 addstat("Adjusted R-squared", `adjr2', "Control Group Mean Turnout"
> , `c_turnout') addtext("Weighted?", Y, "Household-Level Clustered SE?", Y) append
 20.                         }
 21.                         
.                         
.                 }
 22.                 else {                                  // OVER 55 ANALYSIS
 23.                 
.                         * (1) all covs, NO state-by-cov interactions, with hhsize dummies, with ipw
> , with cluster SE
.                         reg voted14 `treat_vars' age age2 age_miss hhsize2 hhsize3 hhsize4 `d_vars'
>  [aweight=`ipw'] if `select' & state == "`s'", vce(cluster hhid)
 24.                         local adjr2 = e(r2_a)
 25.                         qui sum voted14 [aweight=`ipw'] if t2==0 & e(sample)
 26.                         local c_turnout = r(mean)
 27.                         outreg2 using "Table2_ITTEstimatesByState.xls", se bracket dec(3) label 
> ctitle("Over 55 Experiment,`s'") ///
>                                 addstat("Adjusted R-squared", `adjr2', "Control Group Mean Turnout"
> , `c_turnout') addtext("Weighted?", Y, "Household-Level Clustered SE?", Y) append
 28.                 
. 
.                 }
 29. 
. 
.         }
 30.         
.         }
(sum of wgt is   7.5717e+04)

Linear regression                               Number of obs     =     25,223
                                                F(14, 24255)      =      13.29
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0129
                                                Root MSE          =     .37849

                               (Std. Err. adjusted for 24,256 clusters in hhid)
-------------------------------------------------------------------------------
              |               Robust
      voted14 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------+----------------------------------------------------------------
         t3_1 |   .0124287   .0085604     1.45   0.147    -.0043502    .0292075
         t3_2 |   .0069871   .0088606     0.79   0.430    -.0103802    .0243544
          age |  -.0105168   .0021754    -4.83   0.000    -.0147806   -.0062529
         age2 |   .0181668   .0032734     5.55   0.000     .0117506    .0245829
     age_miss |   .2069371   .0900168     2.30   0.022     .0304987    .3833756
      hhsize2 |  -.0250376   .0138663    -1.81   0.071    -.0522164    .0021412
      hhsize3 |  -.0069663   .0601196    -0.12   0.908    -.1248043    .1108718
      hhsize4 |   -.063097   .1092569    -0.58   0.564    -.2772472    .1510532
 d_race_black |  -.0404655   .0073062    -5.54   0.000    -.0547861   -.0261448
  d_race_hisp |  -.0567495   .0115388    -4.92   0.000    -.0793662   -.0341328
 d_race_other |   -.052487   .0157963    -3.32   0.001    -.0834488   -.0215252
d_mar_married |   .1064415     .01609     6.62   0.000     .0749041     .137979
d_mar_unknown |   .0203842   .1140828     0.18   0.858    -.2032251    .2439935
d_gend_female |   .0198738   .0063574     3.13   0.002     .0074128    .0323348
        _cons |   .3058445   .0335017     9.13   0.000      .240179      .37151
-------------------------------------------------------------------------------
Table2_ITTEstimatesByState.xls
dir : seeout
(sum of wgt is   1.0955e+05)

Linear regression                               Number of obs     =     36,503
                                                F(14, 35196)      =      33.76
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0288
                                                Root MSE          =     .36979

                               (Std. Err. adjusted for 35,197 clusters in hhid)
-------------------------------------------------------------------------------
              |               Robust
      voted14 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------+----------------------------------------------------------------
         t3_1 |   .0190242   .0069018     2.76   0.006     .0054964     .032552
         t3_2 |   .0220296   .0071812     3.07   0.002     .0079543     .036105
          age |   .0039388   .0017034     2.31   0.021     .0006001    .0072776
         age2 |  -.0007498   .0025273    -0.30   0.767    -.0057033    .0042037
     age_miss |   .1404861   .0706892     1.99   0.047     .0019331    .2790392
      hhsize2 |   .0240856   .0137179     1.76   0.079    -.0028018    .0509731
      hhsize3 |  -.0115494    .055427    -0.21   0.835     -.120188    .0970892
      hhsize4 |   .0782275    .163121     0.48   0.632    -.2414948    .3979497
 d_race_black |   -.018461   .0060252    -3.06   0.002    -.0302705   -.0066515
  d_race_hisp |  -.0352601   .0090813    -3.88   0.000    -.0530596   -.0174605
 d_race_other |   -.053191   .0100606    -5.29   0.000    -.0729101    -.033472
d_mar_married |   .1184451   .0108179    10.95   0.000     .0972418    .1396485
d_mar_unknown |   .2660084   .0681581     3.90   0.000     .1324163    .3996005
d_gend_female |    .024475   .0051652     4.74   0.000     .0143511     .034599
        _cons |   .0355971   .0267837     1.33   0.184    -.0168997     .088094
-------------------------------------------------------------------------------
Table2_ITTEstimatesByState.xls
dir : seeout
(sum of wgt is   3.8116e+04)
note: hhsize4 omitted because of collinearity

Linear regression                               Number of obs     =     12,719
                                                F(13, 12334)      =      21.23
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0368
                                                Root MSE          =     .42314

                               (Std. Err. adjusted for 12,335 clusters in hhid)
-------------------------------------------------------------------------------
              |               Robust
      voted14 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------+----------------------------------------------------------------
         t3_1 |   .0265677   .0133936     1.98   0.047     .0003141    .0528213
         t3_2 |   .0228626   .0138744     1.65   0.099    -.0043334    .0500586
          age |   .0041326   .0033385     1.24   0.216    -.0024113    .0106766
         age2 |  -.0003231   .0048451    -0.07   0.947    -.0098201     .009174
     age_miss |   .6611662   .0899432     7.35   0.000     .4848634     .837469
      hhsize2 |    .021537   .0256786     0.84   0.402    -.0287971    .0718711
      hhsize3 |   .0088361   .1321768     0.07   0.947     -.250251    .2679232
      hhsize4 |          0  (omitted)
 d_race_black |  -.0102035   .0110194    -0.93   0.354    -.0318033    .0113963
  d_race_hisp |  -.0474629    .020703    -2.29   0.022     -.088044   -.0068819
 d_race_other |  -.0047295    .024159    -0.20   0.845    -.0520849    .0426258
d_mar_married |   .2185567   .0256254     8.53   0.000      .168327    .2687865
d_mar_unknown |  -.2026362   .1128446    -1.80   0.073    -.4238293    .0185569
d_gend_female |     .02904   .0101476     2.86   0.004     .0091491    .0489309
        _cons |    .086339   .0535447     1.61   0.107     -.018617     .191295
-------------------------------------------------------------------------------
Table2_ITTEstimatesByState.xls
dir : seeout
(sum of wgt is   1.1921e+05)
note: d_mar_unknown omitted because of collinearity

Linear regression                               Number of obs     =     39,712
                                                F(13, 38190)      =      21.03
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0147
                                                Root MSE          =     .30412

                               (Std. Err. adjusted for 38,191 clusters in hhid)
-------------------------------------------------------------------------------
              |               Robust
      voted14 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------+----------------------------------------------------------------
         t3_1 |   .0126124   .0053874     2.34   0.019      .002053    .0231718
         t3_2 |   .0127414   .0056001     2.28   0.023     .0017652    .0237177
          age |  -.0152238   .0017063    -8.92   0.000    -.0185683   -.0118794
         age2 |    .023662    .002581     9.17   0.000     .0186032    .0287208
     age_miss |   .0435215   .0927941     0.47   0.639    -.1383573    .2254002
      hhsize2 |  -.0101952   .0087529    -1.16   0.244    -.0273511    .0069606
      hhsize3 |  -.0470456   .0303306    -1.55   0.121    -.1064944    .0124032
      hhsize4 |  -.1863739   .0530428    -3.51   0.000    -.2903392   -.0824087
 d_race_black |   .0026757   .0058418     0.46   0.647    -.0087745    .0141258
  d_race_hisp |   .0031098   .0097785     0.32   0.750    -.0160564    .0222759
 d_race_other |   .0520003   .0090631     5.74   0.000     .0342365    .0697642
d_mar_married |   .0825556    .009244     8.93   0.000     .0644371    .1006742
d_mar_unknown |          0  (omitted)
d_gend_female |   .0217719   .0039095     5.57   0.000     .0141092    .0294346
        _cons |   .2929234   .0267063    10.97   0.000     .2405783    .3452685
-------------------------------------------------------------------------------
Table2_ITTEstimatesByState.xls
dir : seeout
(sum of wgt is   9.0960e+04)
note: d_mar_unknown omitted because of collinearity

Linear regression                               Number of obs     =     30,304
                                                F(11, 29307)      =          .
                                                Prob > F          =          .
                                                R-squared         =     0.0220
                                                Root MSE          =     .37478

                               (Std. Err. adjusted for 29,308 clusters in hhid)
-------------------------------------------------------------------------------
              |               Robust
      voted14 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------+----------------------------------------------------------------
         t3_1 |  -.0039099    .007932    -0.49   0.622    -.0194569    .0116372
         t3_2 |   -.008959   .0082189    -1.09   0.276    -.0250685    .0071504
          age |  -.0046247   .0019973    -2.32   0.021    -.0085394     -.00071
         age2 |    .012935   .0030732     4.21   0.000     .0069114    .0189585
     age_miss |  -.0990567   .0091957   -10.77   0.000    -.1170806   -.0810328
      hhsize2 |   .0119698   .0155168     0.77   0.440    -.0184438    .0423833
      hhsize3 |   .2501231   .1128634     2.22   0.027     .0289058    .4713405
      hhsize4 |   .1016405   .0061235    16.60   0.000     .0896382    .1136428
 d_race_black |  -.0121634   .0068605    -1.77   0.076    -.0256102    .0012835
  d_race_hisp |    -.06527   .0087076    -7.50   0.000    -.0823373   -.0482026
 d_race_other |  -.0015805   .0137787    -0.11   0.909    -.0285873    .0254263
d_mar_married |   .1052435   .0145593     7.23   0.000     .0767066    .1337803
d_mar_unknown |          0  (omitted)
d_gend_female |    .009729   .0057518     1.69   0.091    -.0015447    .0210028
        _cons |   .1969039   .0295523     6.66   0.000       .13898    .2548279
-------------------------------------------------------------------------------
Table2_ITTEstimatesByState.xls
dir : seeout
(sum of wgt is   4.1266e+05)

Linear regression                               Number of obs     =    137,482
                                                F(14, 131070)     =      83.10
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0157
                                                Root MSE          =      .3094

                              (Std. Err. adjusted for 131,071 clusters in hhid)
-------------------------------------------------------------------------------
              |               Robust
      voted14 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------+----------------------------------------------------------------
         t3_1 |   .0074495   .0030523     2.44   0.015     .0014671    .0134318
         t3_2 |   .0053596   .0031704     1.69   0.091    -.0008544    .0115736
          age |    .001169   .0007165     1.63   0.103    -.0002355    .0025734
         age2 |   .0015958   .0010759     1.48   0.138    -.0005129    .0037045
     age_miss |   .1677408   .1164375     1.44   0.150    -.0604745    .3959561
      hhsize2 |   .0143683   .0052542     2.73   0.006     .0040702    .0246663
      hhsize3 |   .0261469   .0202209     1.29   0.196    -.0134857    .0657796
      hhsize4 |   .1093719   .1208197     0.91   0.365    -.1274326    .3461763
 d_race_black |  -.0387713   .0033362   -11.62   0.000    -.0453101   -.0322325
  d_race_hisp |  -.0568867   .0026729   -21.28   0.000    -.0621256   -.0516478
 d_race_other |  -.0474887   .0046654   -10.18   0.000    -.0566328   -.0383446
d_mar_married |   .0633428   .0045207    14.01   0.000     .0544824    .0722032
d_mar_unknown |  -.1587246   .1230679    -1.29   0.197    -.3999355    .0824863
d_gend_female |   .0064832   .0022071     2.94   0.003     .0021573     .010809
        _cons |   .0761923   .0109227     6.98   0.000      .054784    .0976007
-------------------------------------------------------------------------------
Table2_ITTEstimatesByState.xls
dir : seeout
(sum of wgt is   4.9993e+03)
note: t3_2 omitted because of collinearity
note: age_miss omitted because of collinearity
note: hhsize4 omitted because of collinearity
note: d_mar_unknown omitted because of collinearity

Linear regression                               Number of obs     =      2,505
                                                F(9, 2462)        =          .
                                                Prob > F          =          .
                                                R-squared         =     0.0190
                                                Root MSE          =     .45913

                                (Std. Err. adjusted for 2,463 clusters in hhid)
-------------------------------------------------------------------------------
              |               Robust
      voted14 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------+----------------------------------------------------------------
         t3_1 |   .0148178   .0308075     0.48   0.631    -.0455934     .075229
         t3_2 |          0  (omitted)
          age |   .0320639   .0334174     0.96   0.337    -.0334652    .0975929
         age2 |  -.0225997   .0249566    -0.91   0.365    -.0715379    .0263384
     age_miss |          0  (omitted)
      hhsize2 |   .0840159   .1238433     0.68   0.498    -.1588319    .3268637
      hhsize3 |  -.0133573   .0716449    -0.19   0.852    -.1538478    .1271331
      hhsize4 |          0  (omitted)
 d_race_black |   -.067222   .0401343    -1.67   0.094    -.1459224    .0114784
  d_race_hisp |   -.149942   .0605167    -2.48   0.013    -.2686109   -.0312731
 d_race_other |  -.2078453   .0577598    -3.60   0.000    -.3211081   -.0945824
d_mar_married |   .1554614   .0548384     2.83   0.005     .0479273    .2629956
d_mar_unknown |          0  (omitted)
d_gend_female |  -.0064364   .0382245    -0.17   0.866     -.081392    .0685192
        _cons |  -.7760652   1.106465    -0.70   0.483    -2.945763    1.393633
-------------------------------------------------------------------------------
Table2_ITTEstimatesByState.xls
dir : seeout
(sum of wgt is   1.0107e+04)
note: t3_2 omitted because of collinearity
note: age_miss omitted because of collinearity
note: hhsize4 omitted because of collinearity
note: d_mar_unknown omitted because of collinearity

Linear regression                               Number of obs     =      5,091
                                                F(9, 4936)        =          .
                                                Prob > F          =          .
                                                R-squared         =     0.0325
                                                Root MSE          =     .43885

                                (Std. Err. adjusted for 4,937 clusters in hhid)
-------------------------------------------------------------------------------
              |               Robust
      voted14 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------+----------------------------------------------------------------
         t3_1 |   .0349429   .0209045     1.67   0.095    -.0060393    .0759251
         t3_2 |          0  (omitted)
          age |   .0281173   .0188315     1.49   0.135    -.0088007    .0650353
         age2 |  -.0202482   .0136774    -1.48   0.139     -.047062    .0065656
     age_miss |          0  (omitted)
      hhsize2 |   .1294185   .0608788     2.13   0.034     .0100691     .248768
      hhsize3 |  -.3216557   .0325156    -9.89   0.000    -.3854007   -.2579107
      hhsize4 |          0  (omitted)
 d_race_black |  -.0381804   .0299148    -1.28   0.202    -.0968267    .0204659
  d_race_hisp |  -.0497931   .0413662    -1.20   0.229    -.1308893    .0313031
 d_race_other |  -.1524045   .0400432    -3.81   0.000     -.230907    -.073902
d_mar_married |   .1370418   .0324603     4.22   0.000     .0734051    .2006784
d_mar_unknown |          0  (omitted)
d_gend_female |   .0714359   .0218402     3.27   0.001     .0286195    .1142524
        _cons |   -.728783   .6425788    -1.13   0.257    -1.988523    .5309573
-------------------------------------------------------------------------------
Table2_ITTEstimatesByState.xls
dir : seeout
(sum of wgt is   3.4868e+03)
note: t3_2 omitted because of collinearity
note: age_miss omitted because of collinearity
note: hhsize3 omitted because of collinearity
note: hhsize4 omitted because of collinearity
note: d_mar_unknown omitted because of collinearity

Linear regression                               Number of obs     =      1,746
                                                F(9, 1700)        =      19.13
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0846
                                                Root MSE          =     .47836

                                (Std. Err. adjusted for 1,701 clusters in hhid)
-------------------------------------------------------------------------------
              |               Robust
      voted14 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------+----------------------------------------------------------------
         t3_1 |   -.020362   .0376439    -0.54   0.589    -.0941952    .0534712
         t3_2 |          0  (omitted)
          age |   .0584732   .0421946     1.39   0.166    -.0242856    .1412321
         age2 |  -.0403801   .0315745    -1.28   0.201     -.102309    .0215489
     age_miss |          0  (omitted)
      hhsize2 |   .2037589   .0685094     2.97   0.003     .0693873    .3381304
      hhsize3 |          0  (omitted)
      hhsize4 |          0  (omitted)
 d_race_black |   .1618698   .0496401     3.26   0.001     .0645077    .2592319
  d_race_hisp |   .3127962   .0806031     3.88   0.000     .1547044     .470888
 d_race_other |   .1734804   .0956311     1.81   0.070    -.0140867    .3610475
d_mar_married |   .2267983   .0648899     3.50   0.000     .0995258    .3540708
d_mar_unknown |          0  (omitted)
d_gend_female |   .0915238   .0436542     2.10   0.036     .0059021    .1771454
        _cons |  -1.810054   1.398214    -1.29   0.196    -4.552457    .9323484
-------------------------------------------------------------------------------
Table2_ITTEstimatesByState.xls
dir : seeout
(sum of wgt is   6.9423e+03)
note: t3_2 omitted because of collinearity
note: age_miss omitted because of collinearity
note: hhsize4 omitted because of collinearity
note: d_mar_unknown omitted because of collinearity

Linear regression                               Number of obs     =      3,468
                                                F(10, 3414)       =       2.97
                                                Prob > F          =     0.0010
                                                R-squared         =     0.0257
                                                Root MSE          =     .40333

                                (Std. Err. adjusted for 3,415 clusters in hhid)
-------------------------------------------------------------------------------
              |               Robust
      voted14 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------+----------------------------------------------------------------
         t3_1 |  -.0151439   .0231847    -0.65   0.514    -.0606012    .0303134
         t3_2 |          0  (omitted)
          age |   .0662748   .0205839     3.22   0.001     .0259167    .1066329
         age2 |  -.0466367   .0150313    -3.10   0.002     -.076108   -.0171654
     age_miss |          0  (omitted)
      hhsize2 |   .1842296   .1176804     1.57   0.118    -.0465016    .4149607
      hhsize3 |   .1084617   .2303721     0.47   0.638    -.3432195    .5601428
      hhsize4 |          0  (omitted)
 d_race_black |   -.064162   .0325129    -1.97   0.049    -.1279086   -.0004154
  d_race_hisp |   .0413462   .0571222     0.72   0.469     -.070651    .1533433
 d_race_other |  -.0390196   .0393132    -0.99   0.321    -.1160995    .0380602
d_mar_married |   .0677298   .0612611     1.11   0.269    -.0523824     .187842
d_mar_unknown |          0  (omitted)
d_gend_female |   .0112308   .0320971     0.35   0.726    -.0517006    .0741623
        _cons |  -2.087931   .6898943    -3.03   0.002    -3.440578    -.735283
-------------------------------------------------------------------------------
Table2_ITTEstimatesByState.xls
dir : seeout
(sum of wgt is   6.2832e+03)
note: t3_2 omitted because of collinearity
note: age_miss omitted because of collinearity
note: hhsize4 omitted because of collinearity
note: d_mar_unknown omitted because of collinearity

Linear regression                               Number of obs     =      3,146
                                                F(9, 3065)        =          .
                                                Prob > F          =          .
                                                R-squared         =     0.0643
                                                Root MSE          =     .46925

                                (Std. Err. adjusted for 3,066 clusters in hhid)
-------------------------------------------------------------------------------
              |               Robust
      voted14 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------+----------------------------------------------------------------
         t3_1 |    .027991   .0276798     1.01   0.312    -.0262818    .0822638
         t3_2 |          0  (omitted)
          age |   .0660924   .0240144     2.75   0.006     .0190064    .1131784
         age2 |  -.0472794   .0174039    -2.72   0.007    -.0814038    -.013155
     age_miss |          0  (omitted)
      hhsize2 |   .2156259   .0695313     3.10   0.002     .0792933    .3519585
      hhsize3 |  -.4517425   .0617246    -7.32   0.000    -.5727682   -.3307167
      hhsize4 |          0  (omitted)
 d_race_black |   .0716185   .0381196     1.88   0.060     -.003124     .146361
  d_race_hisp |  -.0996402   .0477489    -2.09   0.037    -.1932633   -.0060171
 d_race_other |  -.1171645   .0470984    -2.49   0.013    -.2095121   -.0248169
d_mar_married |    .223429   .0510163     4.38   0.000     .1233995    .3234586
d_mar_unknown |          0  (omitted)
d_gend_female |   .0602486   .0363059     1.66   0.097    -.0109378    .1314351
        _cons |  -1.993297   .8172752    -2.44   0.015     -3.59576   -.3908341
-------------------------------------------------------------------------------
Table2_ITTEstimatesByState.xls
dir : seeout
(sum of wgt is   3.4049e+04)
note: t3_2 omitted because of collinearity
note: age_miss omitted because of collinearity
note: hhsize4 omitted because of collinearity
note: d_mar_unknown omitted because of collinearity

Linear regression                               Number of obs     =     17,023
                                                F(10, 16495)      =      22.40
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0279
                                                Root MSE          =     .40166

                               (Std. Err. adjusted for 16,496 clusters in hhid)
-------------------------------------------------------------------------------
              |               Robust
      voted14 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------+----------------------------------------------------------------
         t3_1 |  -.0172696   .0107409    -1.61   0.108    -.0383229    .0037837
         t3_2 |          0  (omitted)
          age |   .0357443   .0104846     3.41   0.001     .0151933    .0562952
         age2 |  -.0237837   .0077199    -3.08   0.002    -.0389156   -.0086519
     age_miss |          0  (omitted)
      hhsize2 |   .1076563   .0344247     3.13   0.002     .0401802    .1751323
      hhsize3 |  -.1449703   .0222836    -6.51   0.000    -.1886485   -.1012922
      hhsize4 |          0  (omitted)
 d_race_black |  -.0751929   .0170067    -4.42   0.000    -.1085278    -.041858
  d_race_hisp |  -.0917919   .0152635    -6.01   0.000    -.1217099   -.0618739
 d_race_other |  -.1275798   .0190495    -6.70   0.000    -.1649188   -.0902408
d_mar_married |   .0896624   .0160102     5.60   0.000     .0582807    .1210442
d_mar_unknown |          0  (omitted)
d_gend_female |   .0202128   .0110687     1.83   0.068    -.0014831    .0419086
        _cons |  -1.047085   .3513718    -2.98   0.003    -1.735811   -.3583584
-------------------------------------------------------------------------------
Table2_ITTEstimatesByState.xls
dir : seeout

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. restore

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. log close
      name:  <unnamed>
       log:  C:\Users\afang\Documents\PSRM_BallotSecrecy\PublicReplicationArchive\02_Analysis.log
  log type:  text
 closed on:  31 Mar 2017, 14:47:57
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